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Record W2041214192 · doi:10.1177/0008429812469894

Les côtés ténébreux de Mère Teresa

2013· article· en· W2041214192 on OpenAlexaffvenue
Serge Larivée, Carole Sénéchal, Geneviève Chénard

Bibliographic record

VenueStudies in Religion/Sciences Religieuses · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of OttawaUniversité de Montréal
Fundersnot available
KeywordsExorcismMiracleFaithPopularityCriticismPhenomenonPoliticsSociologyReligious studiesTheologyPhilosophyPsychologyEpistemologySocial psychologyArtLiteraturePolitical scienceLaw

Abstract

fetched live from OpenAlex

The impact of Mother Teresa’s work has no religious or geographical boundaries. In the four parts of this text, we try to understand this phenomenon. We first present the method used to collect the available information and then discuss a few biographical considerations to clarify her mission and the media’s contribution to her popularity. The third part identifies four stumbling blocks on her way to canonization: her rather dogmatic religious views, her way of caring for the sick, her political choices, and her suspicious management of funds that she received. Fourth, we discuss some elements of her life related to beatification, including her “night of faith,” the exorcism to which she was subjected as well as the validity of the miracle attributed to her. In conclusion, we question why the criticism of which she has been the target has been ignored by the Vatican.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.093
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.174
GPT teacher head0.495
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2013
Admission routes2
Has abstractyes

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